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The objective of the study is to investigate the dynamic relationship between fiscal stress (FS) shocks and foreign direct investment (FDI) in moderate FS developing countries spanning from 2000 to 2021. The paper seeks to identify dual-regime effects, exploring how FS shocks impact FDI differently in low-stress and high-stress environments.

This study employs advanced econometric techniques to investigate the dynamic relationship between FS shocks and FDI in a sample of moderate FS developing countries spanning from 2000 to 2021. The analysis utilizes variance decomposition, impulse response functions, and a regime-switching vector autoregressive model to explore the nuanced interactions between FS and FDI attraction. These techniques allow for the identification of dual-regime effects, wherein FS shocks exhibit differing impacts on FDI depending on the prevailing stress environment.

The analysis reveals a dual-regime effect of FS shocks on FDI in the sample of moderate FS developing countries studied from 2000 to 2021. In low-stress regimes, FS shocks initially have a positive impact on FDI, suggesting potential investment opportunities. However, in high-stress regimes, the effect reverses, resulting in a negative impact on FDI attraction. Moreover, the study highlights the asymmetric nature of this relationship, with the adverse effects of FS on FDI intensifying over time in high-stress environments.

Previous studies focused mainly on a country's fiscal position and its impact on FDI or capital inflows. This is the first study to assess how FS or fiscal pressure affects FDI.

The purpose of this paper is to scrutinize the safe haven benefits of 13 individual commodities for the USA and Chinese equity sectors during the financial turmoil period. Therefore, sectoral investors in the USA and China could invest in those specific commodities that provide stable returns during the health crisis and financial turmoil periods.

The daily data spans from February 1, 2015, to July 28, 2022. The present study applies several different approaches to analyzing the data set. The author apply the cross-quantilogram (C.Q) methodology to capture the lead-lag bivariate quantile interdependence between two stationary time series variables during the bearish, bullish and normal periods. Then the study used the hedging effectiveness (HE) and conditional diversification benefits (CDB) approaches to capture the hedging and diversification benefits of commodity classes and individual commodities.

The noteworthy findings of the quantilogram methodology reveal that livestock and agriculture commodities serve as better refuges as compared to the precious metals and energy index in both countries. On average, precious metals failed to serve as safe haven investments for the USA and Chinese equity market sectors. All energy commodities except soybean oil had strong comovements with China and the US equity sectors during bearish, bullish and normal periods. Lean hogs, fiddler cattle and live cattle are perfect hedging assets for both countries due to the presence of blue color at normal and bullish periods in all C.Q heat-maps. The HE table depicts that commodity indices and individual commodities failed to serve as hedging assets for the Chinese equity sectors. But commodities are semistrong hedging assets for the US equity sectors and the S&P 500 due to the average HE values being 0.7 and above. The CDB values depict that precious metals provide diversification benefits in both equity markets.

The present study results have important implications for equity sector investors of the USA and China in suggesting particular commodity during the financial turmoil period. During the bearish market condition, risk averse equity sector investors can invest in livestock commodities and agriculture commodities, due to their relatively stable returns. In addition, policymakers can use the analysis insights to formulate policy tools and monitoring mechanisms, effectively mitigating the unfavorable effects arising from asymmetric dependence between commodities and equity sectors during the upper tail, middle and lower tail. Policymakers can suggest equity investors to invest in which commodity during extreme conditions.

The current study has the following points of originality. First, to the best of the author’s knowledge, this is the first study to investigate the individual commodities’ roles as safe havens taken from all four major commodity classes. More importantly, it is also noticeable that the safe haven abilities of commodities are usually tested for the stock market, but the equity sectors are ignored. Therefore, the present study used both stock market and sectoral indices data.

This paper aims to better jointly estimate Value at Risk (VaR) and expected shortfall (ES) by using the joint regression combined forecasting (JRCF) model.

Combining different forecasting models in financial risk measurement can improve their prediction accuracy by integrating the individual models’ information. This paper applies the JRCF model to measure VaR and ES at 5%, 2.5% and 1% probability levels in the Chinese stock market. While ES is not elicitable on its own, the joint elicitability property of VaR and ES is established by the joint consistent scoring functions, which further refines the ES’s backtest. In addition, a variety of backtesting and evaluation methods are used to analyze and compare the alternative risk measurement models.

The empirical results show that the JRCF model outperforms the competing models. Based on the evaluation results of the joint scoring functions, the proposed model obtains the minimum scoring function value compared to the individual forecasting models and the average combined forecasting model overall. Moreover, Murphy diagrams’ results further reveal that this model has consistent comparative advantages among all considered models.

The JRCF model of risk measures is proposed, and the application of the joint scoring functions of VaR and ES is expanded. Additionally, this paper comprehensively backtests and evaluates the competing risk models and examines the characteristics of Chinese financial market risks.

This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.

This research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).

The main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.

Since the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.

The results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.

Previous studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.

Due to excessive carbon dioxide emissions, the world is facing environmental devastation. Energy and environmental innovations are considered to be critical tools in combating the growing CO₂ emissions. Developing these innovations requires extremely high investments in research and development processes, where knowledge is generated as one of the important outputs. This knowledge serves as a basis for innovation development and raising awareness among all relevant stakeholders about excessive environmental degradation. One of the significant sources of knowledge is scientific publications. Therefore, the aim of this research is to examine whether increased CO₂ emissions stimulate the scientific community to publish a greater number of papers, as well as whether the knowledge contained in these publications is utilized in reducing CO₂ emissions. The sample consists of G7 member countries. The time frame of the research is 1996–2019. The dynamic properties of the vector autoregression (VAR) models were summarized using impulse response function and variance decomposition forecast error. In most G7 countries, it has been determined that an increase in scientific production in environmental science and energy leads to a reduction in CO₂ emissions. On the other hand, increased CO₂ emissions affect higher scientific productivity in environmental science and energy only in Canada.

The purpose of the study is to examine how operating efficiencies from incentive alignment compensate for rent extraction in family firms. The author asks whether ownership (1) improves operating efficiencies to increase firm value, (2) positively affects related-party transactions (RPTs), or (3) destroys firm value. Finally, the author assesses whether the incentive effect dominates the entrenchment effect.

This study employs a panel of 333 listed family firms (and 185 nonfamily firms) and handles endogeneity using a dynamic panel system GMM and panel VAR.

Ownership decreases discretionary expenses and increases asset utilization to add firm value. The efficiency gains generate more value in family firms, especially majority-held ones, than in nonmajority ones. However, ownership is also related to increased RPTs (especially dubious loans/guarantees), reducing firm value. RPTs destroy value more severely in the family (or group) firms than in nonfamily (nongroup) firms. It could be why ownership's positive impact on value is lower in family firms than in nonfamily firms. Overall, the incentive effect dominates the entrenchment effect and is robust to controlling private benefits of control in the dynamic ownership-value model.

(1) A family firm's ownership may not be optimal. (2) The firm's long-term commitment as a dynasty limits the scale of expropriation yet sustains impetus for long-term value creation. The paradox partly explains why large family holdings and firm-specific investments endure over generations. (3) This way, large ownership substitutes weak investor protection in India despite tunneling as skin in the game provides necessary investor confidence. (4) Future studies can examine whether extraction varies with family generations and how family characteristics affect the incentive effects.

(1) Concentrated ownership may not be a wrong policy choice in emerging markets to draw firm-specific investments. (2) Investors, auditors, or creditors must pay closer attention to loans/guarantees. (3) More vigorous enforcement, auditor scrutiny, and board oversight are needed.

Family firms are not necessarily a bad organization type that destroys investor wealth. They can be valuably efficient due to their ownership and wealth concentration, and frugality. They matter in the economic growth of a developing market like India.

(1) Extends ownership-performance research to family firms and shows that although ownership facilitates tunneling, the incentive effect dominates; (2) family ownership is not impacted by firm value; (3) family ownership levels reduce discretionary expenses and increase asset utilization to create added value, especially in majority-held family firms; (4) RPTs and loans/guarantees increase with ownership; (5) value erosion from RPTs is higher in family (group) firms than in other firms.

This study empirically investigates the interdependency of select Asian emerging economies along with the financial stress index during the times of the global financial crisis, the Euro crisis and the COVID-19 period. Moreover, it inspects the long-memory effects of the different crises during the study period.

To address the objectives of the study, the authors apply different statistical tools, namely the adjusted correlation coefficient, fractionally integrated generalised autoregressive conditional heteroskedasticity (FIGARCH) model and wavelet coherence model, along with descriptive statistics.

Financial stress is having a prodigious effect on the economic growth of select economies. From the data analysis, it is found that the long-memory effect is noted in the gross domestic product (GDP) for India and Korea only, which implies that the volatility in the GDP series for these two nations demonstrates persistence and dependency on previous values over a lengthy period.

The study is unique of its kind to consider multi-segments within the period of the study to get a clear idea about the effects of the financial stress index on select Asian emerging economies by applying different econometric tools.

This study aims to find whether sukuk (Islamic bonds) possess a safe haven property for investors or not.

To analyze this statement, the study used data from MSCI World conventional and MSCI World Islamic indices from August 17, 2012 to June 8, 2022. The study used the generalized autoregressive conditional heteroskedasticity (GARCH) variance technique, the most common technique used in stock data analysis.

The results dictate the absence of sukuk as a safe haven for investors as both the conventional and Islamic markets show decoupling behavior. The study finds concrete evidence of a strong association between the debt-based bond market and the Islamic sukuk market. As these markets mostly like to move in a parallel direction, a recession in a conventional bond market likely means a recession in the Islamic sukuk market.

This study is unique in incorporating the MSCI World Islamic Index and other Islamic indices of several Muslim countries, which was absent in previous research. Second, this study is unique because it adds a separate regression for the COVID era to show whether the movement of indices changed during regression.

Foreign direct investment (FDI) has a critical role in boosting agricultural productivity and the growth of emerging economies. The relationship between FDI inflows and environmental factors has not received much attention in identifying its impact on agricultural output. Using annual time series data from 1990 to 2023, this study examines the causal association and short- and long-run effects of FDI inflows, forest coverage and CO2 emissions on the agricultural productivity of the India, China and US (ICU) economies. The autoregressive distributed lag (ARDL) results confirmed that FDI inflows have a significant and positive impact on Indian and Chinese agriculture productivity, whereas CO2 emissions adversely affect US agriculture productivity in the long run. In the short run, CO2 emissions led to agricultural productivity in both China and the US economies. The bound test and error correction model (ECM) result also confirmed the long-run connection and convergence of the equilibrium path among the studied variables except India. The findings of the Granger causality test showed a unidirectional causal link between agriculture productivity and FDI inflows and forest coverage in India and a bidirectional causal link between CO2 emission and agricultural yield and forest coverage and CO2 emission in the Chinese agriculture sector. The study also revealed a unidirectional causal association between forest coverage and agricultural output and between FDI, CO2 emissions and forest coverage in the US agriculture sector. Policymakers were advised to encourage FDI in the agriculture sector and expand the use of environment-friendly technology to decrease carbon emissions and promote forest coverage for sustainable growth and higher agricultural production.